Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
High-fidelity Grain Growth Modeling: Leveraging Deep Learning for Fast Computations
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2505.05354.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-11T15:18:46.219931Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation c36b221f-7a3b-4839-9f4e-5a400a52aae6 · inbound
A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics cites this paper.
A Physics-Regulated Neural Framework for Learning 3D Grain Growth Dynamics High-fidelity Grain Growth Modeling: Leveraging Deep Learning for Fast Computations
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T15:18:46.219931Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.